Any discussion of the background art throughout the specification should in no way be considered as an admission that such art is widely known or forms part of common general knowledge in the field.
One of the major sources of image artifacts in computed tomography (CT) is motion of the object of interest, which creates inconsistencies between acquired projections, leading to distortion and blurring when images are reconstructed. For example, in medical CT performed for diagnostic purposes, motion artifacts can lead to false diagnosis. Motion artifacts affect many medical CT medical imaging procedures, such as CT perfusion scans for suspected acute ischemic stroke. They are also a problem in cone beam imaging (for radiotherapy treatment verification), in dental CT, and in some industrial CT imaging applications. Head motion is a common problem in young patients who are often sedated or anesthetized to prevent motion. According to the latest available data, over 70 million medical CT scans are performed annually in the USA alone, of which approximately 10% are performed in children. Moreover, a recent survey of CT practice in developing countries revealed that about 75% of pediatric CT scans were of the head. Due to the relatively high radiation dose associated with CT scanning, it is undesirable to repeat the scan if motion occurs, particularly in children who have a much higher estimated lifetime risk of radiation-induced cancer than adults. In adults, head motion is a problem for patients suffering from claustrophobia or a mental or behavioral incapacity, and in patients with head trauma. In a recent study, head movements classified as moderate or severe were observed in 25% of 103 patients with acute ischemic stroke during CT brain perfusion scans.
In medical CT, a slight movement of the patient will lead to a reduction of spatial resolution, in severe cases resulting in corrupted images unsuitable for diagnosis or further processing. To reduce the likelihood of motion artifacts, medical CT manufacturers have made scanners faster by increasing the number of detector rows and the rate of rotation of the x-ray source and detector, which is not a complete solution. Several motion correction methods have been suggested in the literature, the majority of which are intended for circular cone beam CT (CBCT), and few studies have addressed motion correction for medical multi-slice CT (MSCT) systems. In the latter, the object is often translated axially at a constant speed while the source and detector rotate around it, creating a helical orbit. Motion correction is more tractable in CBCT as the entire object is normally in the field of view at all times. In contrast, with MSCT, the object is always truncated in axial direction, which complicates the application of analytical motion correction algorithms.
Assessment of the object motion is of considerable general interest in tomography. In the medical imaging field, a variety of methods have been applied to the estimation of head motion, including direct motion estimation using a camera system with visual markers or without markers. Artificial or anatomical landmarks can be also tracked in the image or projection domain. Indirect estimation methods have been proposed where motion is estimated through the minimization of errors in consistency conditions using projection moments, or by an iterative process using re-projected image information. Another approach has used similarity measures to quantify changes between projections to measure object motion. Previously, there has been some progress in applying rigid motion correction techniques to helical CT brain scans, by measuring the head motion with a Polaris system (Spectra, Northern Digital Inc, Waterloo, Canada).
Even with these techniques, errors are still visible in the resulting images. The possible reason is that there still is some residual unrecorded motion in each pose, caused by small errors in the pose measurements. “Pose” is a common term in the field, and is used to describe the position and orientation of the portion of the rigid object, e.g. subject/patient, being x-rayed for imaging. Accordingly, a change in a patient's head pose may have six parameters such as three linear translations (x, y, z) and three rotations (about axis x, y, z, for example). These residual, unrecorded changes in pose will result in ‘jagged’ artifacts which are most visible at the edge of the phantom.
It would be desirable to provide for improved processing of CT imagery to reduce the level of motion artifacts.